Searching for missing heritability: Designing rare variant association studies
Open accessAbstract
Significance: Discovering the genetic basis of common diseases, such as diabetes, heart disease, and schizophrenia, is a key goal in biomedicine. Genomic studies have revealed thousands of common genetic variants underlying disease, but these variants explain only a portion of the heritability. Rare variants are also likely to play an important role, but few examples are known thus far, and initial discovery efforts with small sample sizes have had only limited success. In this paper, we describe an analytical framework for the design of rare variant association studies of disease. It provides guidance with respect to sample size, as well as the roles of selection, disruptive and missense alleles, gene-specific allele frequency thresholds, isolated populations, gene sets, and coding vs. noncoding regions.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Analysis of URVs has had limited success in delivering individual gene discovery in schizophrenia because of power limitations, with only a single gene, SETD1A, identified as robustly associated.
“However, the analysis of URVs has had limited success in delivering individual gene discovery in schizophrenia because of power limitations, with only a single gene, SETD1A, identified as robustly associated 13,18 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
The most natural grouping for rare variants is within a gene, based on predicted functional consequence or evidence for deleteriousness.
“The most natural grouping for rare variants is within a gene, based on predicted functional consequence or evidence for deleteriousness 13,14 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
Theory predicts that natural selection will tend to keep large effect risk variants at much lower frequencies in the population, especially in disorders such as schizophrenia that are associated with reduced fecundity.
“Theory predicts that the forces of natural selection will tend to keep large effect risk variants at much lower frequencies in the population, especially in disorders such as schizophrenia that are associated with reduced fecundity 13 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
Because individuals with schizophrenia have fewer offspring, purifying selection is expected to prevent high-risk alleles from reaching even modest allele frequencies.
“Because individuals affected with schizophrenia have fewer offspring, purifying selection is expected to prevent high-risk alleles from reaching even modest allele frequencies6.”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [6]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194 · see citing works
Self-citationFinding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336 · see citing works
Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.
Lander, E. S., & Botstein, D. (1989) · Genetics · doi:10.1093/genetics/121.1.185 · Cited by 5,236 · see citing works
Self-citationCommon SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446 · see citing works
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487 · see citing works
Self-citationSequence Variations in <i>PCSK9,</i> Low LDL, and Protection against Coronary Heart Disease
Cohen, J. C., Boerwinkle, E., Mosley, T. H., & Hobbs, H. H. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054013 · Cited by 3,181 · see citing works
THE NUMBER OF ALLELES THAT CAN BE MAINTAINED IN A FINITE POPULATION
Kimura, M., & Crow, J. F. (1964) · Genetics · doi:10.1093/genetics/49.4.725 · Cited by 2,690 · see citing works
Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test
Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M., & Lin, X. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.05.029 · Cited by 2,317 · see citing works
Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165 · cited 2× · see citing works
“For example, CHD8 was associated with autism with mental retardation (prevalence < 1/300) (52) based on the observation of de novo disruptive mutations in 3 of 1,078 cases (53, 54).”
BackgroundHundreds of variants clustered in genomic loci and biological pathways affect human height
Lango Allen, H., Estrada, K., Lettre, G., Berndt, S. I., Weedon, M. N., Rivadeneira, F., Willer, C. J., Jackson, A. U., Vedantam, S., Raychaudhuri, S., et al. (2010) · Nature · doi:10.1038/nature09410 · Cited by 1,945 · see citing works
Patterns and rates of exonic de novo mutations in autism spectrum disorders
Neale, B. M., Kou, Y., Liu, L., Ma’ayan, A., Samocha, K. E., Sabo, A., Lin, C.-F., Stevens, C., Wang, L.-S., Makarov, V., et al. (2012) · Nature · doi:10.1038/nature11011 · Cited by 1,734 · see citing works
Self-citationMathematical Population Genetics
Baake, E., Ewens, W. J., & Wakolbinger, A. (2006) · Oberwolfach Reports · doi:10.4171/owr/2005/40 · Cited by 1,683 · see citing works
Evolution and functional impact of rare coding variation from deep sequencing of human exomes
Tennessen, J. A., Bigham, A. W., O’Connor, T. D., Fu, W., Kenny, E. E., Gravel, S., McGee, S., Do, R., Liu, X., Jun, G., et al. (2012) · Science · doi:10.1126/science.1219240 · Cited by 1,613 · see citing works
Self-citationMathematical Population Genetics
Ewens, W. J. (2004) · Interdisciplinary applied mathematics · doi:10.1007/978-0-387-21822-9 · Cited by 1,554 · see citing works
The mystery of missing heritability: Genetic interactions create phantom heritability
Zuk, O., Hechter, E., Sunyaev, S. R., & Lander, E. S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1119675109 · Cited by 1,542 · see citing works
Self-citationThe distribution of fitness effects of new mutations
Eyre‐Walker, A., & Keightley, P. D. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2146 · Cited by 1,444 · see citing works
Goldstein, J. L., Schrott, H. G., Hazzard, W. R., Bierman, E. L., & Motulsky, A. G. (1973) · Journal of Clinical Investigation · doi:10.1172/jci107332 · Cited by 1,442 · see citing works
Cohen, J., Pertsemlidis, A., Kotowski, I. K., Graham, R., Garcia, C. K., & Hobbs, H. H. (2005) · Nature Genetics · doi:10.1038/ng1509 · Cited by 1,381 · see citing works
Are Rare Variants Responsible for Susceptibility to Complex Diseases?
Pritchard, J. K. (2001) · The American Journal of Human Genetics · doi:10.1086/321272 · Cited by 1,197 · see citing works
On the allelic spectrum of human disease
Reich, D. E., & Lander, E. S. (2001) · Trends in Genetics · doi:10.1016/s0168-9525(01)02410-6 · Cited by 1,185 · see citing works
Self-citationMultiple Rare Alleles Contribute to Low Plasma Levels of HDL Cholesterol
Cohen, J. C., Kiss, R. S., Pertsemlidis, A., Marcel, Y. L., McPherson, R., & Hobbs, H. H. (2004) · Science · doi:10.1126/science.1099870 · Cited by 1,108 · see citing works
Genome partitioning of genetic variation for complex traits using common SNPs
Yang, J., Manolio, T. A., Pasquale, L. R., Boerwinkle, E., Caporaso, N., Cunningham, J. M., de Andrade, M., Feenstra, B., Feingold, E., Hayes, M. G., et al. (2011) · Nature Genetics · doi:10.1038/ng.823 · Cited by 890 · see citing works
Rare independent mutations in renal salt handling genes contribute to blood pressure variation
Ji, W., Foo, J. N., O'Roak, B. J., Zhao, H., Larson, M. G., Simon, D. B., Newton-Cheh, C., State, M. W., Levy, D., & Lifton, R. P. (2008) · Nature Genetics · doi:10.1038/ng.118 · Cited by 812 · see citing works
Natural selection on protein-coding genes in the human genome
Bustamante, C. D., Fledel-Alon, A., Williamson, S., Nielsen, R., Hubisz, M. J., Glanowski, S., Tanenbaum, D. M., White, T. J., Sninsky, J. J., Hernandez, R. D., et al. (2005) · Nature · doi:10.1038/nature04240 · Cited by 788 · see citing works
National Institute of Diabetes and Digestive Kidney Diseases Inflammatory Bowel Disease Genetics Consortium (NIDDK IBDGC), Rivas, M. A., United Kingdom Inflammatory Bowel Disease Genetics Consortium, International Inflammatory Bowel Disease Genetics Consortium, Beaudoin, M., Gardet, A., Stevens, C., Sharma, Y., Zhang, C. K., Boucher, G., et al. (2011) · Nature Genetics · doi:10.1038/ng.952 · Cited by 771 · see citing works
Self-citationDiffusion models in population genetics
Kimura, M. (1964) · Journal of Applied Probability · doi:10.2307/3211856 · Cited by 771 · see citing works
An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people
Nelson, M. R., Wegmann, D., Ehm, M. G., Kessner, D., St. Jean, P., Verzilli, C., Shen, J., Tang, Z., Bacanu, S.-A., Fraser, D., et al. (2012) · Science · doi:10.1126/science.1217876 · Cited by 647 · see citing works
Assessing the evolutionary impact of amino acid mutations in the human genome.
Boyko, A. R., Williamson, S. H., Indap, A. R., Degenhardt, J. D., Hernandez, R. D., Lohmueller, K. E., Adams, M. D., Schmidt, S., Sninsky, J. J., Sunyaev, S. R., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000083 · Cited by 628 · see citing works
Self-citationKryukov, G. V., Pennacchio, L. A., & Sunyaev, S. R. (2007) · The American Journal of Human Genetics · doi:10.1086/513473 · Cited by 598 · see citing works
Self-citationFarooqi, I. S., & O’Rahilly, S. (2006) · Endocrine Reviews · doi:10.1210/er.2006-0040 · Cited by 583 · see citing works
Testing for an Unusual Distribution of Rare Variants
Neale, B. M., Rivas, M. A., Voight, B. F., Altshuler, D., Devlin, B., Orho‐Melander, M., Kathiresan, S., Purcell, S., Roeder, K., & Daly, M. J. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001322 · Cited by 583 · see citing works
Self-citationEstimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs
The Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ), Lee, S. H., The International Schizophrenia Consortium (ISC), The Molecular Genetics of Schizophrenia Collaboration (MGS), DeCandia, T. R., Ripke, S., Yang, J., Sullivan, P. F., Goddard, M. E., Keller, M. C., et al. (2012) · Nature Genetics · doi:10.1038/ng.1108 · Cited by 579 · see citing works
A mathematical theory of Natural and Artificial Selection
Haldane, J. B. S. (1927) · Mathematical Proceedings of the Cambridge Philosophical Society · doi:10.1017/s0305004100011750 · Cited by 577 · see citing works
Recent Explosive Human Population Growth Has Resulted in an Excess of Rare Genetic Variants
Keinan, A., & Clark, A. G. (2012) · Science · doi:10.1126/science.1217283 · Cited by 548 · see citing works
Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia
Johansen, C. T., Wang, J., Lanktree, M. B., Cao, H., McIntyre, A. D., Ban, M. R., Martins, R. A., Kennedy, B. A., Hassell, R. G., Visser, M. E., et al. (2010) · Nature Genetics · doi:10.1038/ng.628 · Cited by 437 · see citing works
Self-citationRomeo, S., Wu, Y., Kozlitina, J., Pennacchio, L. A., Boerwinkle, E., Hobbs, H. H., & Cohen, J. C. (2008) · Journal of Clinical Investigation · doi:10.1172/jci37118 · Cited by 422 · see citing works
The distribution of fitness effects of new deleterious amino acid mutations in humans.
Eyre-Walker, A., Woolfit, M., & Phelps, T. (2006) · Genetics · doi:10.1534/genetics.106.057570 · Cited by 377 · see citing works
Exome sequencing and the genetic basis of complex traits
Kiezun, A., Garimella, K., Do, R., Stitziel, N. O., Neale, B. M., McLaren, P. J., Gupta, N., Sklar, P., Sullivan, P. F., Moran, J. L., et al. (2012) · Nature Genetics · doi:10.1038/ng.2303 · Cited by 372 · see citing works
Self-citationClan Genomics and the Complex Architecture of Human Disease
Lupski, J. R., Belmont, J. W., Boerwinkle, E., & Gibbs, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.09.008 · Cited by 366 · see citing works
Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes
The Meta-Analysis of Glucose and Insulin-Related Traits Consortium (MAGIC), Bonnefond, A., Clément, N., Fawcett, K., Yengo, L., Vaillant, E., Guillaume, J.-L., Dechaume, A., Payne, F., Roussel, R., et al. (2012) · Nature Genetics · doi:10.1038/ng.1053 · Cited by 363 · see citing works
Keightley, P. D., & Eyre‐Walker, A. (2007) · Genetics · doi:10.1534/genetics.107.080663 · Cited by 358 · see citing works
Marth, G., Czabarka, É., Murvai, J., & Sherry, S. T. (2004) · Genetics · doi:10.1534/genetics.166.1.351 · Cited by 324 · see citing works
Jobling, M. A., Hurles, M. E., & Tyler‐Smith, C. (2019) · Garland Science eBooks · doi:10.1201/9780203487211 · Cited by 318 · see citing works
Levy‐Lahad, E., Catane, R., Eisenberg, S., Kaufman, B., Hornreich, G., Lishinsky, E., Shohat, M., Weber, B., Beller, U., Lahad, A., et al. (1997) · Europe PMC (PubMed Central) · Cited by 316 · see citing works
Abortion surveillance--United States, 1999.
Elam–Evans, L. D., Strauss, L. T., Herndon, J. L., Parker, W. Y., Whitehead, S. J., & Berg, C. J. (2002) · PubMed · Cited by 308 · see citing works
Li, Y., Vinckenbosch, N., Tian, G., Huerta‐Sánchez, E., Jiang, T., Jiang, H., Albrechtsen, A., Andersen, G., Cao, H., Korneliussen, T. S., et al. (2010) · Nature Genetics · doi:10.1038/ng.680 · Cited by 307 · see citing works
Seventy-five genetic loci influencing the human red blood cell
van der Harst, P., Zhang, W., Leach, I. M., Rendon, A., Verweij, N., Sehmi, J., Paul, D. S., Elling, U., Allayee, H., Li, X., et al. (2012) · Nature · doi:10.1038/nature11677 · Cited by 306 · see citing works
Sequencing studies in human genetics: design and interpretation
Goldstein, D. B., Allen, A. S., Keebler, J., Margulies, E. H., Petrou, S., Petrovski, S., & Sunyaev, S. R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3455 · Cited by 254 · see citing works
Self-citationMedical Sequencing at the Extremes of Human Body Mass
Ahituv, N., Kavaslar, N., Schackwitz, W., Ustaszewska, A., Martin, J., Hébert, S., Doelle, H., Ersoy, B. A., Kryukov, G. V., Schmidt, S., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/513471 · Cited by 221 · see citing works
Self-citationComparison of statistical tests for disease association with rare variants
Basu, S., & Pan, W. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20609 · Cited by 215 · see citing works
Power of deep, all-exon resequencing for discovery of human trait genes
Kryukov, G. V., Shpunt, A., Stamatoyannopoulos, J. A., & Sunyaev, S. R. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0812824106 · Cited by 156 · see citing works
Self-citationComputational and statistical approaches to analyzing variants identified by exome sequencing
Stitziel, N. O., Kieżun, A., & Sunyaev, S. R. (2011) · Genome biology · doi:10.1186/gb-2011-12-9-227 · Cited by 137 · see citing works
Self-citationWhole-genome sequence–based analysis of high-density lipoprotein cholesterol
Morrison, A. C., Liu, X., Li, A., Boerwinkle, E., Voorman, A., Rice, K. M., Johnson, A. D., O’Donnell, C. J., Cupples, L. A., Yu, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2671 · Cited by 126 · see citing works
Haukka, J., Suvisaari, J., & Lönnqvist, J. (2003) · American Journal of Psychiatry · doi:10.1176/appi.ajp.160.3.460 · Cited by 126 · see citing works
Ladouceur, M., Dastani, Z., Aulchenko, Y. S., Greenwood, C. M. T., & Richards, J. B. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002496 · Cited by 107 · see citing works
McGee, T. L., Devoto, M., Ott, J., Berson, E. L., & Dryja, T. P. (1997) · The American Journal of Human Genetics · doi:10.1086/301614 · Cited by 106 · see citing works
Distribution of the strength of selection against amino acid replacements in human proteins.
Yampolsky, L. Y., Kondrashov, F. A., & Kondrashov, A. S. (2005) · Human Molecular Genetics · doi:10.1093/hmg/ddi350 · Cited by 95 · see citing works
Diogo, D., Kurreeman, F. A. S., Stahl, E. A., Liao, K. P., Gupta, N., Greenberg, J. D., Rivas, M. A., Hickey, B., Flannick, J. A., Thomson, B. P., et al. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.11.012 · Cited by 93 · see citing works
Self-citationSmall fitness effect of mutations in highly conserved non-coding regions
Kryukov, G. V., Schmidt, S., & Sunyaev, S. R. (2005) · Human Molecular Genetics · doi:10.1093/hmg/ddi226 · Cited by 82 · see citing works
Self-citationMendelian disorders and multifactorial traits: the big divide or one for all?
Antonarakis, S. E., Chakravarti, A., Cohen, J. C., & Hardy, J. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2793 · Cited by 80 · see citing works
The Strength of Selection on Ultraconserved Elements in the Human Genome
Chen, C. T. L., Wang, J. C. C., & Cohen, B. A. (2007) · The American Journal of Human Genetics · doi:10.1086/513149 · Cited by 70 · see citing works
Inferring causality and functional significance of human coding DNA variants
Sunyaev, S. R. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds385 · Cited by 50 · see citing works
Self-citation
Flagged first, then by citations
1 of the 65 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
The Ensembl Variant Effect Predictor
McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099 · see citing works
FinnGen provides genetic insights from a well-phenotyped isolated population
Kurki, M. I., Karjalainen, J., Palta, P., Sipilä, T. P., Kristiansson, K., Donner, K. M., Reeve, M. P., Laivuori, H., Aavikko, M., Kaunisto, M. A., et al. (2023) · Nature · doi:10.1038/s41586-022-05473-8 · Cited by 4,233 · see citing works
Genetics of diabetes mellitus and diabetes complications
Cole, J. B., & Florez, J. C. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0278-5 · Cited by 1,797 · see citing works
Fritsche, L. G., Igl, W., Bailey, J. N. C., Grassmann, F., Sengupta, S., Bragg-Gresham, J. L., Burdon, K. P., Hebbring, S. J., Wen, C., Gorski, M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3448 · Cited by 1,544 · see citing works
Guidelines for investigating causality of sequence variants in human disease
MacArthur, D. G., Manolio, T. A., Dimmock, D. P., Rehm, H. L., Shendure, J., Abecasis, G. R., Adams, D. R., Altman, R. B., Antonarakis, S. E., Ashley, E. A., et al. (2014) · Nature · doi:10.1038/nature13127 · Cited by 1,224 · see citing works
Self-citationRare-Variant Association Analysis: Study Designs and Statistical Tests
Lee, S., Abecasis, G. R., Boehnke, M., & Lin, X. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.06.009 · Cited by 1,042 · see citing works
The UK10K project identifies rare variants in health and disease
The UK10K Consortium, Writing group, Walter, K., Min, J. L., Huang, J., Crooks, L., Memari, Y., McCarthy, S., Perry, J. R. B., Xu, C., et al. (2015) · Nature · doi:10.1038/nature14962 · Cited by 1,040 · see citing works
Exome sequencing and analysis of 454,787 UK Biobank participants
Backman, J., Li, A. H., Marcketta, A., Sun, D., Mbatchou, J. S., Kessler, M. D., Benner, C., Liu, D., Locke, A. E., Balasubramanian, S., et al. (2021) · Nature · doi:10.1038/s41586-021-04103-z · Cited by 915 · see citing works
Rare coding variants in ten genes confer substantial risk for schizophrenia
Singh, T., Poterba, T., Curtis, D., Akil, H., Al Eissa, M., Barchas, J. D., Bass, N., Bigdeli, T. B., Breen, G., Bromet, E. J., et al. (2022) · Nature · doi:10.1038/s41586-022-04556-w · Cited by 983 · see citing works
Self-citationPsychiatric Genomics: An Update and an Agenda
Sullivan, P. F., Agrawal, A., Bulik, C. M., Andreassen, O. A., Børglum, A. D., Breen, G., Cichon, S., Edenberg, H. J., Faraone, S. V., Gelernter, J., et al. (2018) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2017.17030283 · Cited by 676 · see citing works
Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, A. V., & Kathiresan, S. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.160 · Cited by 659 · see citing works
Self-citationRare and low-frequency coding variants alter human adult height
Marouli, E., Graff, M., Medina-Gomez, C., Lo, K. S., Wood, A. R., Kjaer, T. R., Fine, R. S., Lu, Y., Schurmann, C., Highland, H. M., et al. (2017) · Nature · doi:10.1038/nature21039 · Cited by 610 · see citing works
Statistical power and significance testing in large-scale genetic studies
Sham, P. C., & Purcell, S. M. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3706 · Cited by 573 · see citing works
Dewey, F. E., Murray, M. F., Overton, J. D., Habegger, L., Leader, J. B., Fetterolf, S. N., O’Dushlaine, C. T., Hout, C. V. V., Staples, J. C., Gonzaga-Jauregui, C. G., et al. (2016) · Science · doi:10.1126/science.aaf6814 · Cited by 533 · see citing works
Gazal, S., Finucane, H. K., Furlotte, N. A., Loh, P.-R., Palamara, P. F., Liu, X., Schoech, A., Bulik-Sullivan, B., Neale, B. M., Gusev, A., et al. (2017) · Nature Genetics · doi:10.1038/ng.3954 · Cited by 525 · see citing works
Self-citationZhou, X., Feliciano, P., Shu, C., Wang, T., Astrovskaya, I., Hall, J. B., Obiajulu, J. U., Wright, J. R., Murali, S. C., Xu, S. X., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01148-2 · Cited by 453 · see citing works
The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders
Smoller, J. W. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.266 · Cited by 479 · see citing works
ANGPTL3 deficiency and protection against coronary artery disease
Stitziel, N. O., Khera, A. V., Wang, X., Bierhals, A. J., Vourakis, A. C., Sperry, A. E., Natarajan, P., Klarin, D., Emdin, C. A., Zekavat, S. M., et al. (2017) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2017.02.030 · Cited by 467 · see citing works
Self-citationDissecting the genetics of complex traits using summary association statistics
Paşaniuc, B., & Price, A. L. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.142 · Cited by 444 · see citing works
Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
Sullivan, P. F., & Geschwind, D. H. (2019) · Cell · doi:10.1016/j.cell.2019.01.015 · Cited by 452 · see citing works
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Loh, P.-R., Bhatia, G., Gusev, A., Finucane, H. K., Bulik-Sullivan, B. K., Pollack, S. J., de Candia, T. R., Lee, S. H., Wray, N. R., et al. (2015) · Nature Genetics · doi:10.1038/ng.3431 · Cited by 449 · see citing works
Self-citationIncreased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia
Genovese, G., Fromer, M., Stahl, E. A., Ruderfer, D. M., Chambert, K., Landén, M., Moran, J. L., Purcell, S. M., Sklar, P., Sullivan, P. F., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4402 · Cited by 444 · see citing works
Using high-resolution variant frequencies to empower clinical genome interpretation
Whiffin, N., Minikel, E., Walsh, R., O’Donnell-Luria, A. H., Karczewski, K., Ing, A. Y., Barton, P. J. R., Funke, B., Cook, S. A., MacArthur, D., et al. (2017) · Genetics in Medicine · doi:10.1038/gim.2017.26 · Cited by 441 · see citing works
“6,7 It is intuitively apparent that when assessing a variant for a causative role in a dominant Mendelian disease, the frequency of a variant in a reference sample, not selected for the condition, should not exceed the prevalence of the condition.”
BackgroundExcessive burden of lysosomal storage disorder gene variants in Parkinson’s disease
Robak, L. A., Jansen, I. E., van Rooij, J., Uitterlinden, A. G., Kraaij, R., Jankovic, J., Heutink, P., Shulman, J. M., International Parkinson’s Disease Genomics Consortium (IPDGC), Nalls, M. A., et al. (2017) · Brain · doi:10.1093/brain/awx285 · Cited by 433 · see citing works
Inactivating Mutations in <i>NPC1L1</i> and Protection from Coronary Heart Disease
The Myocardial Infarction Genetics Consortium Investigators (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1405386 · Cited by 419 · see citing works
Kurki, M., Karjalainen, J. M., Palta, P., Sipila, T. P., Kristiansson, K., Donner, K. M., Reeve, M. P., Laivuori, H. M., Aavikko, M., Kaunisto, M. A., et al. (2022) · medRxiv · doi:10.1101/2022.03.03.22271360 · Cited by 405 · see citing works
Psychiatric genetics and the structure of psychopathology
Smoller, J. W., Andreassen, O. A., Edenberg, H. J., Faraone, S. V., Glatt, S. J., & Kendler, K. S. (2019) · Molecular Psychiatry · doi:10.1038/s41380-017-0010-4 · Cited by 398 · see citing works
Variant interpretation: functional assays to the rescue
Starita, L. M., Ahituv, N., Dunham, M. J., Kitzman, J. O., Roth, F. P., Seelig, G., Shendure, J., & Fowler, D. M. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.07.014 · Cited by 381 · see citing works
Sidore, C., Busonero, F., Maschio, A., Porcu, E., Naitza, S., Żołędziewska, M., Mulas, A., Pistis, G., Steri, M., Danjou, F., et al. (2015) · Nature Genetics · doi:10.1038/ng.3368 · Cited by 376 · see citing works
Factors influencing success of clinical genome sequencing across a broad spectrum of disorders
Taylor, J. C., Martin, H. C., Lise, S., Broxholme, J., Cazier, J., Rimmer, A., Kanapin, A. A., Lunter, G. A., Fiddy, S., Allan, C., et al. (2015) · Nature Genetics · doi:10.1038/ng.3304 · Cited by 376 · see citing works
A population genetic interpretation of GWAS findings for human quantitative traits
Simons, Y. B., Bullaughey, K., Hudson, R. R., & Sella, G. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2002985 · Cited by 363 · see citing works
Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions
Grubert, F., Zaugg, J. B., Kasowski, M., Ursu, O., Spacek, D. V., Martin, A. R., Greenside, P., Srivas, R., Phanstiel, D. H., Pekowska, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.07.048 · Cited by 319 · see citing works
Epigenetic inheritance and the missing heritability
Trerotola, M., Relli, V., Simeone, P., & Alberti, S. (2015) · Human Genomics · doi:10.1186/s40246-015-0041-3 · Cited by 318 · see citing works
“However, simple models of additive effects of ever-smaller components have remained as yet unproven [4–7].”
BackgroundMaccaferri, M., Zhang, J., Bulli, P., Abate, Z., Chao, S., Cantù, D., Bossolini, E., Chen, X., Pumphrey, M., & Dubcovsky, J. (2015) · G3 Genes Genomes Genetics · doi:10.1534/g3.114.014563 · Cited by 315 · see citing works
Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans
Saykin, A. J., Shen, L., Yao, X., Kim, S., Nho, K. T., Risacher, S. L., Ramanan, V. K., Foroud, T., Faber, K. M., Sarwar, N., et al. (2015) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2015.05.009 · Cited by 301 · see citing works
Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls
Platform, B. G., Flannick, J., DiscovEHR Collaboration, CHARGE, LuCamp, ProDiGY, GoT2D, ESP, SIGMA-T2D, T2D-GENES, et al. (2019) · Nature · doi:10.1038/s41586-019-1231-2 · Cited by 304 · see citing works
Moon, S., Kim, Y. J., Han, S., Hwang, M. Y., Shin, D. M., Park, M. Y., Lu, Y., Yoon, K., Jang, H.-M., Kim, Y. K., et al. (2019) · Scientific Reports · doi:10.1038/s41598-018-37832-9 · Cited by 290 · see citing works
Measuring missing heritability: Inferring the contribution of common variants
Golan, D., Lander, E. S., & Rosset, S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1419064111 · Cited by 288 · see citing works
Self-citationGenome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation
Teumer, A., Chaker, L., Groeneweg, S., Li, Y., Di Munno, C., Barbieri, C., Schultheiss, U. T., Traglia, M., Ahluwalia, T. S., Akiyama, M., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06356-1 · Cited by 280 · see citing works
Extreme Polygenicity of Complex Traits Is Explained by Negative Selection
O'Connor, L. J., Schoech, A. P., Hormozdiari, F., Gazal, S., Patterson, N., & Price, A. L. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.07.003 · Cited by 268 · see citing works
Li, X., Li, Z., Zhou, H., Gaynor, S. M., Liu, Y., Chen, H., Sun, R., Dey, R., Arnett, D. K., Aslibekyan, S. W., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0676-4 · Cited by 242 · see citing works
Self-citationThe genetics of bipolar disorder
Gordovez, F. J. A., & McMahon, F. J. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0634-7 · Cited by 268 · see citing works
Rare variant association studies: considerations, challenges and opportunities
Auer, P. L., & Lettre, G. (2015) · Genome Medicine · doi:10.1186/s13073-015-0138-2 · Cited by 246 · see citing works
Global Genetic Networks and the Genotype-to-Phenotype Relationship
Costanzo, M., Kuzmin, E., van Leeuwen, J., Mair, B., Moffat, J., Boone, C., & Andrews, B. (2019) · Cell · doi:10.1016/j.cell.2019.01.033 · Cited by 241 · see citing works
Genetics of Common, Complex Coronary Artery Disease
Musunuru, K., & Kathiresan, S. (2019) · Cell · doi:10.1016/j.cell.2019.02.015 · Cited by 241 · see citing works
Self-citationGenome‐wide association study of schizophrenia in Ashkenazi Jews
Goes, F. S., McGrath, J., Avramopoulos, D., Wolyniec, P., Pirooznia, M., Ruczinski, I., Nestadt, G., Kenny, E. E., Vacic, V., Peters, I., et al. (2015) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32349 · Cited by 226 · see citing works
Genetics of coronary artery disease and myocardial infarction
Dai, X. (2016) · World Journal of Cardiology · doi:10.4330/wjc.v8.i1.1 · Cited by 226 · see citing works
Next-generation sequencing in Charcot–Marie–Tooth disease: opportunities and challenges
Pipis, M., Rossor, A., Laurá, M., & Reilly, M. (2019) · Nature Reviews Neurology · doi:10.1038/s41582-019-0254-5 · Cited by 188 · see citing works
Monogenic and polygenic determinants of sarcoma risk: an international genetic study
Ballinger, M. L., Goode, D. L., Ray-Coquard, I. L., James, P. A., Mitchell, G., Niedermayr, E., Puri, A., Schiffman, J. D., Dite, G. S., Cipponi, A., et al. (2016) · The Lancet Oncology · doi:10.1016/s1470-2045(16)30147-4 · Cited by 214 · see citing works
Missing heritability of complex diseases: case solved?
Génin, E. (2019) · Human Genetics · doi:10.1007/s00439-019-02034-4 · Cited by 210 · see citing works
Lu, Q., Hu, Y., Sun, J., Cheng, Y., Cheung, K., & Zhao, H. (2015) · Scientific Reports · doi:10.1038/srep10576 · Cited by 191 · see citing works
Grarup, N., Sandholt, C. H., Hansen, T. F., & Pedersen, O. B. (2014) · Diabetologia · doi:10.1007/s00125-014-3270-4 · Cited by 201 · see citing works
MVP predicts the pathogenicity of missense variants by deep learning
Qi, H., Zhang, H., Zhao, Y., Chen, C., Long, J. J., Chung, W. K., Guan, Y., & Shen, Y. (2021) · Nature Communications · doi:10.1038/s41467-020-20847-0 · Cited by 198 · see citing works
Association of rare and common variation in the lipoprotein lipase gene with coronary artery disease
Khera, A. V., Won, H.-H., Peloso, G. M., O’Dushlaine, C., Liu, D., Stitziel, N. O., Natarajan, P., Nomura, A., Emdin, C. A., Gupta, N., et al. (2017) · JAMA · doi:10.1001/jama.2017.0972 · Cited by 198 · see citing works
Self-citationWessel, J., Chu, A. Y., Willems, S. M., Wang, S., Yaghootkar, H., Brody, J. A., Dauriz, M., Hivert, M., Raghavan, S., Lipovich, L., et al. (2015) · Nature Communications · doi:10.1038/ncomms6897 · Cited by 192 · see citing works
Palla, L., & Dudbridge, F. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.06.005 · Cited by 185 · see citing works
Li, C., Zhi, D., Wang, K., & Liu, X. (2022) · Genome Medicine · doi:10.1186/s13073-022-01120-z · Cited by 192 · see citing works
Deep-coverage whole genome sequences and blood lipids among 16,324 individuals
Natarajan, P., Peloso, G. M., Zekavat, S. M., Montasser, M. E., Ganna, A., Chaffin, M. D., Khera, A. V., Zhou, W., Bloom, J. M., Engreitz, J., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05747-8 · Cited by 178 · see citing works
Self-citationExome sequencing of Finnish isolates enhances rare-variant association power
Locke, A. E., Steinberg, K. M., Chiang, C. W. K., Service, S. K., Havulinna, A. S., Stell, L., Pirinen, M., Abel, H., Chiang, C., Fulton, R. S., et al. (2019) · Nature · doi:10.1038/s41586-019-1457-z · Cited by 170 · see citing works
Evidence of directional and stabilizing selection in contemporary humans
Sanjak, J. S., Sidorenko, J., Robinson, M. R., Thornton, K., & Visscher, P. M. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707227114 · Cited by 179 · see citing works
From variant to function in human disease genetics
Lappalainen, T., & MacArthur, D. G. (2021) · Science · doi:10.1126/science.abi8207 · Cited by 175 · see citing works
Osborne, A. J., Breno, M., Borsa, N. G., Bu, F., Frémeaux‐Bacchi, V., Gale, D. P., van den Heuvel, L. P., Kavanagh, D., Noris, M., Pinto, S., et al. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1701695 · Cited by 172 · see citing works
Uncovering the Genetic Architecture of Major Depression
McIntosh, A. M., Sullivan, P. F., & Lewis, C. M. (2019) · Neuron · doi:10.1016/j.neuron.2019.03.022 · Cited by 160 · see citing works
Understanding inflammatory bowel disease via immunogenetics
de Lange, K. M., & Barrett, J. C. (2015) · Journal of Autoimmunity · doi:10.1016/j.jaut.2015.07.013 · Cited by 166 · see citing works
Common Methods for Performing Mendelian Randomization
Teumer, A. (2018) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2018.00051 · Cited by 165 · see citing works
Association mapping in plants in the post-GWAS genomics era
Gupta, P. K., Kulwal, P. L., & Jaiswal, V. (2019) · Advances in genetics · doi:10.1016/bs.adgen.2018.12.001 · Cited by 163 · see citing works
High-Diversity Mouse Populations for Complex Traits
Saul, M. C., Philip, V. M., Reinholdt, L. G., & Chesler, E. J. (2019) · Trends in Genetics · doi:10.1016/j.tig.2019.04.003 · Cited by 165 · see citing works
Gazal, S., Loh, P.-R., Finucane, H. K., Ganna, A., Schoech, A., Sunyaev, S., & Price, A. L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0231-8 · Cited by 154 · see citing works
Self-citationLuo, Y., de Lange, K. M., Jostins, L., Moutsianas, L., Randall, J., Kennedy, N. A., Lamb, C. A., McCarthy, S., Ahmad, T., Edwards, C., et al. (2017) · Nature Genetics · doi:10.1038/ng.3761 · Cited by 162 · see citing works
Schoech, A. P., Jordan, D. M., Loh, P.-R., Gazal, S., O’Connor, L. J., Balick, D. J., Palamara, P. F., Finucane, H. K., Sunyaev, S. R., & Price, A. L. (2019) · Nature Communications · doi:10.1038/s41467-019-08424-6 · Cited by 157 · see citing works
Self-citationGenetic studies of alcohol dependence in the context of the addiction cycle
Reilly, M. T., Noronha, A., Goldman, D. A., & Koob, G. F. (2017) · Neuropharmacology · doi:10.1016/j.neuropharm.2017.01.017 · Cited by 155 · see citing works
The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits
Lohmueller, K. E. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004379 · Cited by 152 · see citing works
Identification of individuals by trait prediction using whole-genome sequencing data
Lippert, C., Sabatini, R., Maher, M. C., Kang, E. Y., Lee, S., Arıkan, O., Harley, A. S., Bernal, A., Garst, P., Lavrenko, V. P., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1711125114 · Cited by 154 · see citing works
Human Semaphorin 3 Variants Link Melanocortin Circuit Development and Energy Balance
van der Klaauw, A. A., Croizier, S., de Oliveira, E. M., Stadler, L. K. J., Park, S., Kong, Y., Banton, M. C., Tandon, P., Hendricks, A. E., Keogh, J. M., et al. (2019) · Cell · doi:10.1016/j.cell.2018.12.009 · Cited by 153 · see citing works
Singh, T., Neale, B. M., & Daly, M. J. (2020) · doi:10.1101/2020.09.18.20192815 · Cited by 980 · see citing works
“Theory predicts that the forces of natural selection will tend to keep large effect risk variants at much lower frequencies in the population, especially in disorders such as schizophrenia that are associated with reduced fecundity 13 .”
BackgroundSelf-citationType 2 diabetes: genetic data sharing to advance complex disease research
Flannick, J. A., & Florez, J. C. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.56 · Cited by 145 · see citing works
Bennett, B. J., Davis, R. C., Civelek, M., Orozco, L. D., Wu, J., Qi, H., Pan, C., Packard, R. R. S., Eskin, E., Yan, M., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005711 · Cited by 135 · see citing works
Zhu, N., Pauciulo, M. W., Welch, C. L., Lutz, K. A., Coleman, A. W., Gonzaga-Jauregui, C. G., Wang, J., Grimes, J. M., Martin, L. J., He, H., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0685-z · Cited by 136 · see citing works
Ramanan, V. K., Risacher, S. L., Nho, K., Kim, S., Shen, L., McDonald, B. C., Yoder, K. K., Hutchins, G. D., West, J. D., Tallman, E. F., et al. (2015) · Brain · doi:10.1093/brain/awv231 · Cited by 133 · see citing works
Schmid‐Hempel, P. (2021) · doi:10.1093/oso/9780198832140.001.0001 · Cited by 130 · see citing works
The use of electronic health records for psychiatric phenotyping and genomics
Smoller, J. W. (2017) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32548 · Cited by 125 · see citing works
Whole-genome analyses of whole-brain data: working within an expanded search space
Medland, S. E., Jahanshad, N., Neale, B. M., & Thompson, P. M. (2014) · Nature Neuroscience · doi:10.1038/nn.3718 · Cited by 119 · see citing works
Self-citationUtility of long-read sequencing for All of Us
Mahmoud, M., Huang, Y., Garimella, K. V., Audano, P. A., Wan, W., Prasad, N., Handsaker, R. E., Hall, S., Pionzio, A., Schatz, M. C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-44804-3 · Cited by 115 · see citing works
Genetic contributions to bipolar disorder: current status and future directions
O’Connell, K. S., & Coombes, B. J. (2021) · Psychological Medicine · doi:10.1017/s0033291721001252 · Cited by 115 · see citing works
A random forest approach to capture genetic effects in the presence of population structure
Stephan, J., Stegle, O., & Beyer, A. (2015) · Nature Communications · doi:10.1038/ncomms8432 · Cited by 107 · see citing works
Sehgal, D., Autrique, E., Singh, R. P., Ellis, M., Singh, S., & Dreisigacker, S. (2017) · Scientific Reports · doi:10.1038/srep41578 · Cited by 111 · see citing works
Quantifying the impact of rare and ultra-rare coding variation across the phenotypic spectrum
Ganna, A., Satterstrom, F. K., Zekavat, S. M., Das, I., Kurki, M. I., Churchhouse, C., Alfoldi, J., Martin, A. R., Havulinna, A. S., Byrnes, A., et al. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.05.002 · Cited by 110 · see citing works
Self-citationMahajan, A., Sim, X., Ng, H. J., Manning, A. K., Rivas, M. A., Highland, H. M., Locke, A. E., Grarup, N., Im, H. K., Cingolani, P., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1004876 · Cited by 110 · see citing works
Exome Sequencing of Familial Bipolar Disorder
Goes, F. S., Pirooznia, M., Parla, J. S., Kramer, M., Ghiban, E., Mavruk, S., Chen, Y.-C., Monson, E. T., Willour, V. L., Karchin, R., et al. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2016.0251 · Cited by 107 · see citing works
Genetics of Type 2 Diabetes: Implications from Large-Scale Studies
DeForest, N., & Majithia, A. R. (2022) · Current Diabetes Reports · doi:10.1007/s11892-022-01462-3 · Cited by 112 · see citing works
Genetic studies of Crohn's disease: Past, present and future
Liu, J. Z., & Anderson, C. A. (2014) · Best Practice & Research Clinical Gastroenterology · doi:10.1016/j.bpg.2014.04.009 · Cited by 104 · see citing works
Josephs, E. B., Stinchcombe, J. R., & Wright, S. (2017) · New Phytologist · doi:10.1111/nph.14410 · Cited by 107 · see citing works
Enhancer Domains Predict Gene Pathogenicity and Inform Gene Discovery in Complex Disease
Wang, X., & Goldstein, D. B. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.01.012 · Cited by 99 · see citing works
Discovering genetic interactions bridging pathways in genome-wide association studies
Fang, G., Wang, W., Paunić, V., Heydari, H., Costanzo, M., Liu, X., Liu, X., VanderSluis, B., Oately, B., Steinbach, M. S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12131-7 · Cited by 101 · see citing works
Genetics of Venous Thrombosis: update in 2015
Suchon, P., Trégouët, D., & Morange, P. (2015) · Thrombosis and Haemostasis · doi:10.1160/th15-05-0410 · Cited by 102 · see citing works
Genetics of the dentofacial variation in human malocclusion
Uribe, L. M. M., & Miller, S. F. (2015) · Orthodontics and Craniofacial Research · doi:10.1111/ocr.12083 · Cited by 101 · see citing works
Ganna, A., Genovese, G., Howrigan, D. P., Byrnes, A., Kurki, M., Zekavat, S. M., Whelan, C. W., Kals, M., Nivard, M. G., Bloemendal, A., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4404 · Cited by 101 · see citing works
Self-citationGoodrich, J. K., Singer‐Berk, M., Son, R. G., Sveden, A., Wood, J. C., England, E. M., Cole, J. B., Weisburd, B., Watts, N., Caulkins, L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23556-4 · Cited by 100 · see citing works
Predicting functional effect of missense variants using graph attention neural networks
Zhang, H., Xu, M. S., Fan, X., Chung, W. K., & Shen, Y. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00561-w · Cited by 98 · see citing works
Genotype–Phenotype Correlation — Promiscuity in the Era of Next-Generation Sequencing
Lu, J. T., Campeau, P. M., & Lee, B. (2014) · New England Journal of Medicine · doi:10.1056/nejmp1400788 · Cited by 96 · see citing works
- Authors
- Zuk, O., Schaffner, S. F., Samocha, K., Do, R., Hechter, E., Kathiresan, S., Daly, M. J., Neale, B. M., Sunyaev, S. R., & Lander, E. S.
- Affiliations
- Broad Institute (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-01-17
- Volume
- 111
- Issue
- 4
- Pages
- E455-64
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3910587
- OpenAlex
- W1986818660
- Cited by
- 635
- References
- 65
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 36 · 2023: 40 · 2022: 35 · 2021: 64 · 2020: 41 · 2019: 59 · 2018: 52 · 2017: 71 · 2016: 86 · 2015: 70 · 2014: 48 · 2013: 1 · 2012: 2
- FWCI
- 59.70
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- National Human Genome Research Institute (U54HG003067)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- missing heritability, research design, sample size, isolated populations, gene set analysis, de novo mutations, selection coefficients, replication
- MeSH terms
- Gene Frequency, Humans, Mutation, Genetic Variation, Genetic Predisposition to Disease, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review